Unusual usage alerts

ABSTRACT

Techniques for unusual usage alerts without smart meter data are provided. The computing device can determine a set of climate control disaggregation coefficients and obtain weather data corresponding to at least a portion of a billing period. In turn, the computing device can determine first forecasted usage data for the at least a portion of the billing period based on the set of climate control disaggregation coefficients and the weather data, and determine second forecasted usage data for a length of the billing period based at least in part on the first forecasted usage data. In some aspects, the computing device can project unusual energy usage for the billing period based on the second forecasted usage data determined to be greater than usage data for a prior time period. The computing device can generate an alert notification including an indication of the unusual energy usage projection.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of priority to U.S.Provisional Application No. 62/019,822, filed Jul. 1, 2014, entitled“UNUSUAL USAGE ALERTS WITHOUT SMART METER DATA,” which is herebyincorporated by reference in its entirety.

BACKGROUND

The subject technology relates to data processing systems, and inparticular, to unusual usage alerts without smart meter data.

With smart meter data, an alert can be sent to customers before the endof a billing period, for example, to alert the customers of a projectedhigh bill amount, allowing them time to change their behavior before theconclusion of the billing cycle. As such, alerts based on smart meterdata can help provide advanced notifications to customers that have ahigh likelihood of receiving a large bill, e.g., before the bill isissued. Unexpectedly higher bills have several ill effects, includingincreased customer churn (in competitive markets where customers mayselect a resource provider from a number of different choices),increased call volume, and/or an increase in late or partial payments,especially for customers on limited or fixed incomes.

SUMMARY

In some aspects, the subject technology relates to a computing devicefor generating and sending unusual usage alerts, without the use ofsmart meter data. In some implementations, the computing device includesat least one processor and a memory for storing instructions that, whenexecuted by the processor, cause the computing device to performspecified operations including, determining a set of climate controldisaggregation coefficients associated with energy consumption data of acommodity for a utility customer. The set of climate controldisaggregation coefficients may include one or more coefficientsrelating to a rate of energy consumption for a corresponding type ofclimate control. In some aspects, the computing device obtains weatherdata for at least a portion of a billing period, and uses the weatherdata to determine first forecasted usage data for the billing periodbased on the climate control disaggregation coefficients. In someaspects, second forecasted usage data is determined for a length of thebilling period based on the first forecasted usage data, and an unusualenergy usage projection is determined for the utility customer if thesecond forecasted usage data is greater than usage data for a prior timeperiod corresponding to the billing period. In some aspects, thecomputing device can be further configured to generate an alertnotification including the unusual energy usage projection.

In another aspect, the subject technology relates to a method forgenerating unusual usage alerts. Depending on the desiredimplementation, the method can include steps for determining a set ofclimate control disaggregation coefficients associated with energyconsumption data of a commodity for a utility customer, and determiningfirst weather data for a first portion of a billing period. In someimplementations, the method can further include steps for determining afirst forecasted usage for the first portion of the billing period basedon the climate control disaggregation coefficients and the first weatherdata, and determining second weather data corresponding to a secondportion of the billing period. In such aspects, the second portion maybe subsequent in time to that of the first portion. In turn, the methodcan further include steps for determining a second forecasted usage forthe second portion of the billing period based on the set of climatecontrol disaggregation coefficients and the second weather data. Assuch, an unusual energy usage projection for the particular utilitycustomer can be determined, for example, based on a combination of thefirst forecasted usage and the second forecasted usage being greaterthan usage data for a prior time period corresponding to the billingperiod. Additionally, in some aspects, an alert notification can begenerated, wherein the alert notification includes an indication of theunusual energy usage projection.

In still another aspect, the subject technology relates to anon-transitory computer readable storage medium for storing instructionsfor generating unusual usage alerts using a computing device. Dependingon implementation, the instructions, when executed by a processor, cancause the computing device to execute operations, including, determininga set of climate control disaggregation coefficients associated withenergy consumption data of a commodity for a utility customer, andobtaining weather data corresponding to a portion of a billing period.In some implementations, the computing may be further configured todetermine first forecasted usage data for at least a portion of thebilling period, for example, based on the set of climate controldisaggregation coefficients and the weather data. In another approach,the computing device can determine second forecasted usage data for alength of the billing period based on the first forecasted usage data,and determine an unusual energy usage projection for the utilitycustomer based on the second forecasted usage data being greater thanusage data for a prior time period corresponding to the billing period.

In some aspects, the computing device can be configured to determine ifthe unusual energy usage projection or an actual usage projection,indicate that a utility bill for the particular utility customer isgreater than a threshold. The actual usage projection may relate toactual usage data associated with one or more utility customers similarto the particular utility customer. The computing device can generate analert notification including an indication of the unusual energy usageprojection. In some aspects, the indication can include informationrelating to a cause for an increase in the utility bill based on theunusual energy usage projection and/or the actual usage projectiondetermined to be greater than the threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following description, reference is made to the followingfigures, and in which are shown by way of illustration specificembodiments in which the subject technology may be practiced. It is tobe understood that other embodiments may be utilized and changes may bemade without departing from the scope of the subject technology.

FIG. 1 illustrates an example of an energy usage alert system, accordingto certain aspects of the subject technology.

FIGS. 2-4 illustrate flowcharts of example processes for unusual usagealerts without smart meter data in the energy usage alert systemdescribed in FIG. 1, according to certain aspects of the technology.

FIGS. 5A-5C illustrates examples of energy usage alert notifications,according to certain aspects of the technology.

FIG. 6 illustrates an example of an environment for implementing aspectsof the technology.

FIG. 7 illustrates an example of a system for energy usage alerts,according to certain aspects of the technology.

FIG. 8 illustrates an example configuration of components of a computingdevice, according to certain aspects of the technology.

DETAILED DESCRIPTION

The detailed description set forth below is intended as a description ofvarious configurations of the subject technology and is not intended torepresent the only configurations in which the subject technology can bepracticed. The appended drawings are incorporated herein and constitutea part of the detailed description. The detailed description includesspecific details for the purpose of providing a more thoroughunderstanding of the subject technology. However, it will be clear andapparent that the subject technology is not limited to the specificdetails set forth herein and may be practiced without these details. Insome instances, structures and components are shown in block diagramform in order to avoid obscuring the concepts of the subject technology.

Aspects of the subject technology enable a system to determine that acustomer may experience unusual resource usage (e.g., higher energyconsumption) for a billing period based on climate information and, inresponse, provide an alert notification to the customer before the endof the billing period or before the customer receives the bill for thatperiod. The subject technology may be implemented in systems that do notuse a smart meter to measure customer resource (e.g., energy) usage and,in fact, provides a technical solution to a number of technical problemswith systems that do not use smart meters to provide unusual usage alertnotifications before the end of a billing period.

A smart meter is a device that records the consumption or use ofresources (e.g., electricity) at particular time intervals. Depending onthe implementation, various time intervals may be used. For example, asmart meter may be configured to record resource consumption levels oncean hour, once every 15 minutes, once every minute, or some otherinterval. Smart meters may also be configured to transmit data (e.g.,resource usage interval data), for example, to utility servers via anetwork, such as the Internet. The smart meter data may be transmittedin real time or in batches.

In contrast to smart meters, other resource meters do not transmit usagedata in between measuring events (e.g., billing periods). Some technicallimitations of systems not using smart meters stem from the inability toobtain usage data before the end of a billing period using these otherresource meters. Due to the unavailability of recent consumption data(e.g., within a current billing period) it has been difficult todetermine if the customer's usage rate is unusual, in turn, preventingthe ability to provide an alert/notification to indicate the unusualusage before the end of the billing period.

Aspects of the subject technology address these and other technicalproblems by providing ways to determine (or project) an unusual resourceusage for a customer, for example, using historic consumption andweather data. In some aspects, a level of sensitivity for resourceusage, with respect to corresponding weather changes is used todetermine, climate control disaggregation coefficients that can be usedto help project or predict future resource consumption. Accordingly,weather data and the level of sensitivity may be used instead of (or inaddition to) power load data. It is understood that aspects of thetechnology can be implemented without the use of smart meters, and insome implementations, smart meter data may be used to facilitate aspectsof the subject technology.

As described herein “systems” of the subject technology may beimplemented using one or more servers, a climate control device, acomputing device (which may or may not be in communication with theclimate control device or other appliance), a mobile device, and/or acombination of devices.

As used herein, “usage” refers to a quantity of use, a cost associatedwith the use, and/or a quantified metric representing the use or cost.The term “actual energy usage” refers to a meter reading or a usagereading. The term “commodity” refers to a utility-based commodity, suchas electricity, water, or natural gas, which are consumable resourcesdelivered to an entity, dwelling or commercial structure. The term“component of a property” refers to a component associated with theproperty that is able to consume a commodity. One example of a componentof a property may be a heating, ventilation and air conditioning (HVAC)system that controls the climate within the property using electricity,natural gas, and/or another energy commodity. The component may relateto one or more of a central heating device, a central air conditioningand heating system, an appliance, an electronic device, water heatingsystem, a power generating device, a ventilation system, or an airfiltration system, etc.

FIG. 1 illustrates an example of an energy usage alert system 100,according to certain aspects of the subject technology. Energy usagealert system 100 includes a utility management system 104 and a billingmanagement system 108. In some aspects, management system 104 can becoupled to utility customers 101-1 via monitoring devices 102-1 and/orclimate control devices 103-1. Depending on implementation, monitoringdevices 102-1 may be non-Advanced Metering Infrastructure (AMI) basedpower metering devices, such as monitoring devices 102-2 a-102-2 n.Alternatively, management system 104 may be associated with utilitycustomers (e.g., 101-1 a-101-1 n) via an AMI-based monitoring device or“smart metering device” such as monitoring devices 102-1 a-102-1 n.Similarly, the utility management system 104 can be associated withutility customers 101-2 via any of communication channels 115, includingbut not limited to: climate control devices 103-1 n, mail service 117and/or dispatch device 118.

In the example of FIG. 1, utility management system 104 includes usagedatabase 105, billing operation module 106 and forecasted usage datadatabase 107. In turn, billing management system 108 includesdisaggregation coefficient module 109, rate module 110, forecast module111, monitor module 112, report module 113, recommendation module 114and weather module 116. Billing management system 108 may conveyinformation targeted to one or more of the utility customers 101-1a-101-1 n and 101-2 a-101-2 n over communication channels 115.

Communication channels 115 include climate control device(s) 103-1 n,mail service 117 and dispatch device 118; however, other communicationchannels may be implemented. Climate control device(s) 103-1 n caninclude various devices, such as “smart thermostats,” configured toprovide information output in a location associated with thepower-consuming customer. In some approaches, mail service 117 may be aprint service, for example, that is configured for printingnotifications/communications that are provided by report module 113, toone or more of utility customers 101-1 a-101-1 n.

Utility management system 104 stores usage data in the usage database105. In some aspects, usage data is associated with one or morecommodities consumed by utility customers 101-1 a-101-1 n. As usedherein, usage data can include usage information corresponding toamounts of resource consumption for at least one of the one or morecommodities for multiple utility customers (e.g., utility customers101-1 a . . . 101-1 n, or 101-2 a . . . 101-2 n).

It is understood that usage data can be collected or aggregated fromvarious reading types, including one-directional interval readingswherein usage data is provided to a utility or other data collector atcertain time intervals (e.g., once per billing cycle, once per month, oron a weekly basis etc.

Independent of the collection method used, usage data can relate to amonetary amount of actual usage to date (e.g., a monetary value ($20))or an amount of energy used (e.g., 1.4 kWh) in the billing period. Theusage information may include past usage information of the commoditye.g., for one or more completed billing periods. In someimplementations, usage data (e.g., “usage interval data”) includes usageinformation corresponding to billed usage of at least one commodity formultiple utility customers (e.g., utility customers 101-2 a, 101-2 b . .. 101-2 n) without smart meter data. There exists a technical problemwherein the non-smart meter data limits sending the alert to thecorresponding utility customers until the end of the billing period.This and other technical problems are addressed by the subjecttechnology.

In some aspects, usage data for a utility customer is obtained from acorresponding monitoring device on a scheduled basis, periodic basis ora non-scheduled basis. Historic usage data may also be associated withcustomers, or the site at which the commodity is consumed. For example,usage interval data for electric power may be associated with aparticular customer (e.g., a customer account) or may be associated witha location (e.g., a residence or business) where the electric power isused or consumed.

In practice, utility management system 104 stores and forwards usagedata to the billing management system 108 for usage alert processing.Utility management system 104 described herein may be implemented by autility company or an offsite third party service provider interfacedwith the utility company.

In some aspects, utility management system 104 stores projected usageinformation in forecasted usage data database 107. The projected usageinformation may be based on the usage data and estimated usage for aremaining amount of time in the current billing period. For example, thebilling operation module 106 may obtain the usage data to determine arate of use for the corresponding utility customer. Depending onimplementation, the rate of use can be based on the amount of energyconsumed over a specified time period, such as a predetermined number ofdays. The rate of use may be applied to the remaining amount of time todetermine the estimated usage. As such, the projected usage informationmay consist of the usage data to date and the estimated usage for theremaining time in the billing period. A more detailed description of theprojected use determination is described in FIG. 2.

In some approaches, disaggregation coefficient module 109 is configuredto determine a set of climate control disaggregation coefficientsrelating to one or more of utility customers 101-1 a-101-1 n and 101-2a-101-2 n, e.g., with respect to one or more billing periods. In anaspect, the disaggregation coefficient module 109 includes an interfaceto monitoring devices 102-1 a-102-1 n and 102-2 a-102-2 n, for example,to associate three coefficients (e.g., base-load, cooling, heating) foreach meter. Examples of energy disaggregation are described in U.S. Pat.No. 8,660,813, which is hereby incorporated by reference in itsentirety.

Rate module 110 may store a local copy of a rate schedule associatedwith the fees for commodities provided by the utility company. In someaspects, rate module 110 is configured to obtain the rate scheduleassociated with the current billing period, from the utility company,e.g., via a network such as the Internet. In turn, forecast module 111is configured to determine the projected use of energy (e.g., an energyuse forecast) by utility customers 101-1 a-101-1 n and 101-2 a-101-2 nbased on the corresponding usage data (e.g., non-AMI data or AMI data).The forecast module 111 may perform a process configured to determinethe projected usage information using rate of use information andbilling period information.

In some implementations, monitor module 112 includes an interface tomonitoring devices 102-1 a-102-1 n and 102-2 a-102-2 n, e.g., to obtainusage data directly and/or include an interface with utility managementsystem 104, for example, to receive usage data for further processing byone or more components of billing management system 108 (e.g., projecteduse information, rate of use information). Likewise, report module 113may be configured to generate a usage alert notification, and cause theusage alert notification to be sent to one or more of the utilitycustomers 101 a-101 n based on one or more reporting conditions,including but not limited to, unusual usage alert caused byweather-related usage, projected bill exceeding a target budget, currentbilling period ended, utility customer inquiry, etc. Recommendationmodule 114 may be configured to generate one or more recommendations forreducing an unusually high utility bill or for steps that may be takentowards power conservation.

The weather module 116 may be configured to obtain weather data (e.g.,past weather conditions and forecasted weather conditions) from a thirdparty weather service, for example, via an application programminginterface (API). In an aspect, weather module 116 is configured to fetchdata relating to forecasted weather conditions, for example, based onhistorical weather data of a corresponding geographic location and timeperiod.

Communication channels 115 may carry alert notifications to the utilitycustomers 101-1 a-101-1 n and 101-2 a-101-2 n over wired and/or awireless communication channels. In an aspect, the billing managementsystem 108 sends the alert notifications in a broadcast and/or multicastsignal to the utility customers 101-1 a-101-1 n and 101-2 a-101-2 n viaclimate control devices 103-1 n. In another aspect, alert notificationsmay be sent to one or more of utility customers 101-1 a-101-1 n and101-2 a-101-2 n using a print service and/or mail provider, such as mailservice 117. In yet another aspect, other communication channels such asshort messaging service (SMS), email, and or automated-telephone dialingmay be used, for example via dispatch device 118, which can includevarious hardware and software modules, as well as network connectivitynecessary for dispatching electronic alert notifications.

In some implementations, billing management system 108 may specificallytarget one or more of the utility customers 101-1 a-101-1 n and/or 101-2a-101-2 n, and send personalized alert notifications using a unicastsignal. The communication channels 115 may be configured to interfacewith a mothering device, such as any of monitoring devices 102-1 a-102-1n, e.g., via smart meter, and/or a utility meter, such as, monitoringdevices 102-2 a-102-2 n and/or a thermostat (e.g., climate controldevice 103-1 n a customer's mobile device, a data exchange interface ofa cellular network, and/or other networks.

In operation, energy usage alert system 100 allows for predictingwhether or not utility customers will receive an unusual bill (e.g., ahigher than expected bill) at the end of a billing cycle (or period)using a set of climate control disaggregation coefficients applied to acorresponding utility customer 101. For example, energy usage alertsystem 100 can calculate a projected energy use for a particular billingcycle, using the disaggregation coefficients for the utility customer101, and based on the retrieved usage data for that utility customer. Inresponse to the detection of an abnormally high energy use (andconsequently a high bill), a usage alert communication can be sent to aclient computing device associated with that utility customer, forexample, if the projected use is determined to be greater than aprevious billing period by a threshold amount. That is, usage alerts maybe prevented (not sent) if the projected total consumption is below apredetermined threshold, for example, indicating that the customer'sincreased usage was not significant, or alternatively that the increasedusage corresponded with expected changes in weather (e.g., particularlyhot days).

In certain implementations, the usage alert communication may providerecommendations on how to reduce the utility bill for the remainingportion of the billing period, and/or provide information explainingpossible causes for the projected high utility bill even if no smartmeter data is obtainable from the utility customer site (e.g.,monitoring device 102-2). That is, content of the usage alert may vary,depending on the targeted customer, and may provide various types ofinformation to provide guidance on how to reduce a bill amount for thecurrent period, as well as to educate the customer as to potentialcauses of the abnormally high power consumption.

FIG. 2 illustrates a flowchart of an example process 200 for energyusage alerts in the energy usage alert system described in FIG. 1,according to certain aspects of the subject technology. Process 200 isprovided merely as an example and additional or fewer steps may beperformed in a similar or alternative order, or in parallel, withoutdeparting from the scope of the technology.

Process 200 begins with step 210, in which a computing device (e.g., thebilling management system 108) can determine a set of climate controlcoefficients (e.g., disaggregation coefficients) associated with energyconsumption data for a particular customer/consumer. Because climatecontrol disaggregation coefficients are determined using historic usedata, some of the contextual examples discussed below describe thedetermination of climate control disaggregation coefficients for aparticular utility customer, for example, with respect to theconsumption of electric power. However, it is understood that any entityor consumer may be included. By way of example, disaggregationcoefficients may be calculated for any type of “power consumer,” whichmay describe various individuals, groups, organizations and/or physicalbuildings or locations where electric power is provided and/or consumed.

In some aspects, disaggregation coefficients are calculated using aseries of historic use values (e.g., power consumption values), andtheir associated outdoor temperature values over a defined time period.For example, month-by-month home energy consumption values can beassociated with outdoor temperature values (such as an average monthlytemperature) for each corresponding home/building. It is understood thathistoric use values can represent power consumption measurements takenat various time intervals, such as on a per-billing-cycle, amonth-by-month, week-by-week, or hour-by-hour basis.

Once a series of energy use values and outdoor temperature values aredetermined, a series of temperature difference values for the timeperiod are determined based on differences in temperature between eachof the outdoor temperature values and one or more baseline temperatures.Although some aspects are described as having one baseline temperaturefor both heating and cooling, in other aspects more baselinetemperatures may be used (e.g., a heating baseline temperature and acooling baseline temperature). In some aspects, the baseline temperaturecan be predetermined (chosen) as a temperature that is generallycomfortable to humans (e.g., room temperature, or a customer'sthermostat set point for heating/cooling). Thus, the baselinetemperature can be chosen as having a value between 55° F. and 75° F.However, the baseline temperature can vary based on geography and userpreferences, depending on the desired implementation.

Once the baseline temperature is determined, a series of cooling degreevalues and heating degree values are calculated. Cooling degree valuescan be calculated by subtracting the baseline temperature from outdoortemperatures that are above the baseline. Conversely, heating degreevalues are determined by subtracting outdoor temperatures (that areabove the baseline), from the baseline temperature. The resultingheating/cooling degree values each correspond with an energy use valueand outdoor temperature value, as discussed above.

Using the temperature difference values (i.e., heating degree valuesand/or cooling degree values), a regression analysis can be performed todetermine one or more climate-control coefficients and a non-climatecontrol coefficient. Climate-control coefficients are representative ofclimate-control related energy use. In contrast, a non-climate controlcoefficient is representative of non-climate control energy use, suchas, energy used for entertainment, cooking and/or lighting, etc.

To determine climate control coefficients, the temperature differencevalues are plotted against the corresponding energy use values. Using anordinary least squares regression analysis, the slopes of the resultinglines represent the respective climate control coefficients. That is,the line resulting from a graph of the heating degree values (as plottedagainst the energy use values), has a slope representing the climatecontrol coefficient for the heating degree values. Likewise, a lineresulting from a graph of the cooling degree values, as plotted againstthe energy use values, will have a slope representing the climatecontrol coefficient for the cooling degree values.

In the above example, the non-climate control coefficient can bedetermined where the resulting lines cross the axis on which the energyuse values are plotted, that is, where the temperature difference iszero (which may be either the vertical or horizontal axis, depending onthe chosen graphical orientation). For example, when the respectivehome/building is not being heated or cooled (i.e., the temperaturedifference value is “0”), then the remaining energy usage is fornon-climate related activities, indicating for example, energy useattributable activities other than heating/cooling of the building.

On the other hand, the cooling coefficient and heating coefficient arerepresentative of the building's energy sensitivity with respect tochanges in outside temperature. In other words, the cooling coefficientand heating coefficient model the amount of energy necessary to cool orheat the building given a particular outdoor temperature (e.g., a dailyaverage outdoor temperature).

The non-climate control coefficient, cooling coefficient, and heatingcoefficient can be location specific (e.g., associated with a residenceor building) and, therefore, calculated separately. Separatecalculations for each coefficient (e.g., on a building-by-building)basis can also be performed because one building's sensitivity tooutdoor temperature may be less than (or greater than) that of adifferent building. For example, one household may have an efficientHVAC system with well insulated walls and windows etc., whereas anotherhousehold may have an outdated cooling and heating system with poorinsulation. Furthermore, non-climate control energy use may vary betweenbuildings.

Example processes for calculating a non-climate control coefficient, acooling coefficient and a heating coefficient are disclosed by U.S.Patent Application Publication 2011/0106471, entitled “Method and Systemfor Disaggregating Heating and Cooling Energy Use from Other BuildingEnergy Use,” filed Nov. 5, 2010, which is hereby incorporated byreference in its entirety.

Once the non-climate control coefficient, cooling coefficient, andheating coefficient are determined, they can be used to determine aclimate control energy use and non-climate control energy use. Theclimate control energy use and a non-climate control energy use can bedetermined from a set of equations. For example, a total calculation ofheating energy use can be calculated using equation 1, below:

HeatingEnergyUse=HeatingCoefficient*sum(HeatingDegreeValues)  (1)

Similarly, a total calculation of cooling energy use is given byequation 2, below:

CoolingEnergyUse=CoolingCoefficient*sum(CoolingDegreeValues)  (2)

As such, a calculation for the total climate control energy use can bedetermined by equation 3:

ClimateControlEnergyUse=HeatingEnergyUse+CoolingEnergyUse  (3)

That is, the heating energy use plus the cooling energy use is equal tothe climate control energy use. As such, the non-climate control energyuse can be calculated using equation 4.

Non-climateControlEnergyUse=TimeInterval*Non-ClimateControlCoefficient  (4)

In the above example, the climate control coefficient includes both acooling coefficient and a heating coefficient. In other aspects,however, the climate control coefficient may include only a heatingcoefficient or only a cooling coefficient. For example, in some cases,there may only be a cooling coefficient because there are no heatingdegree values. In such cases, the heating coefficient would have a valueof “0.”

In step 220, the computing device can obtain, for example, from a thirdparty service provider, weather data corresponding to at least a portionof a billing period. The computing device may obtain the weatherinformation from the third party service provider (e.g., InternationalWeather Service) via an application programming interface (API).Information from the third party service provider may belatitude/longitude based. In some aspects, the weather information maybe obtained from cached results of neighboring service provider sites(e.g., weather stations) such that requests from a client computingdevice for sites in proximity of one another can be served by the samecached results. In an aspect, the computing device obtains weather datafrom a data structure containing weather conditions for specified timesand corresponding geographic locations.

In step 230, the computing device can determine an energy use for aprevious time period, for example, within the current billing period(e.g., “first forecasted usage data”). That is, the first forecastedusage data provides an indication of the amount (or cost) of currentenergy, i.e., a period-to-date usage.

In this example, the first forecasted usage data can be determined usingan expression defined as:

period_to_date_days*coefficient_(base-load)+period_to_date_cooling_degree_days*coefficient_(cooling)+period_to_date_heating_degree_days*coefficient_(heating),

In the above expression, the period_to_date_cooling_degree_daysrepresents a summation of a series of temperature difference values fordays in the previous time period in which the temperature was higherthan the baseline temperature. Similarly, theperiod_to_date_heating_degree_days, corresponds with a summation of aseries of temperature difference values for days in the previous timeperiod in which the temperature was lower than the correspondingbaseline. The coefficient_(base-load) represents the base-loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.

In step 240, the computing device can determine second forecasted usagedata, representing an expected amount of energy consumption for somefuture time period, e.g., the time period spanning a remaining portionof a current billing period. In some aspects, the second forecastedusage data can be determined based on a scaling of the first forecastedusage data, discussed above. For example, if the first forecasted usagedata provides a consumption estimate for the first ¼ of a currentbilling period, the second forecasted usage data may be calculated byscaling the first forecasted usage data (e.g., the second forecastedusage data may be estimated to be three times the first forecasted usagedata amount).

The second forecasted usage data may be expressed as a monetary value oran amount of energy used for the billing period. Furthermore, the secondforecasted usage data may be related to the cost or amount of energyused by a property and/or the cost or amount of energy used by one (ormore) energy consumption components (e.g., an appliance, an HVAC system,electric-vehicle, etc.) of the property.

Depending on implementation, the second forecasted usage data may bebased on the first forecasted usage data being scaled by an expectednumber of days remaining in the billing period. Further to the aboveexample, the first forecasted usage may be calculated on a day-by-daybasis. As such, the second forecasted usage may be calculated by scalingthe first forecasted usage based on a number of days remaining in thebilling period. For example, if the remaining billing period is twice aslong as the time period for the first forecasted usage estimation, thesecond forecasted usage data may represent a power usage estimate thatis twice as large as that of the first forecasted usage data.

In an alternative embodiment, the second forecasted usage may be basedon weather forecast information for the associated time period, i.e., afuture time period or a remaining duration of a current billing cycle.That is, weather forecast data for a future time period may be used todetermine temperature difference estimates for each remaining day in thetime period. Using these temperature difference estimates, as well aspreviously calculated cooling/heating coefficients, second forecast datacan be calculated, as discussed above.

In step 250, the computing device can perform operations to determine anunusual energy usage projection for the particular utility customer, forexample, based on the second forecasted usage data. In someimplementations, the second forecasted usage data may be consideredunusual (e.g., unusually high) if the projected energy use exceeds apredetermined threshold consumption amount (e.g., 30% more than theutility customer's average consumption amount of the past 3 billingcycles, 15% more than an average consumption amount for similar users,etc.). In other implementations, the second forecasted usage data mayindicate an unusually high consumption if the second forecasted usageexceeds consumption for a previous, but comparable, time period (e.g.,the same period in a preceding year or billing cycle).

In some aspects, forecasted weather conditions may also be taken intoaccount when determining if a forecasted usage is to be consideredunusual. For example, if weather changes warrant additional energyexpenditure (e.g., on either heating or cooling), then the forecastedusage may not be considered to be ‘unusual’ even if the energy usage ishigher than for a previous, but comparable, time period.

In some aspects, the computing device can apply a rate structure to thesecond forecasted usage data to determine a forecasted bill amountcorresponding to the length of the billing period. That is, a cost ratefor each unit of energy (e.g., kW/h) may be multiplied by the totalestimated usage (e.g., based on the second forecasted usage data). Assuch, a forecasted bill amount can be determined, for example, byperforming a similar calculation for energy already consumed (e.g., fora prevision fraction of the billing period) and combining the cost withan cost estimated based on total estimated usage, as discussed above.The unusual energy usage projection for the particular utility customeris based at least in part on the forecasted bill amount being greaterthan a bill amount for the prior time period.

In step 260, the computing device can generate an alert notification,including an indication of the unusual energy usage projection, and sendthe alert notification to the particular utility customer. In thisrespect, the unusual energy usage projection can relate to a likelihoodthat the particular utility customer is projected to receive a utilitybill that is higher than expected. For example, if the currentforecasted usage or billed amount is more than the same period in aprevious time period (plus some specified margin or threshold amount),then an alert is sent to the customer to indicate that they are on trackfor an unusually high utility bill.

In certain aspects, the computing device may provide recommendations inthe alert notification regarding how to modify usage so that theprojected bill amount will fall within the expectations of the customerfor the billing period. Recommendations may include set points or setpoint schedules that can be used on the climate control device, such asa smart thermostat, to reduce usage. For example, using thermodynamicmodeling and/or hourly or daily weather forecast data, the HVAC runtimebased on a current thermostat setting can be determined including howmuch the HVAC runtime can be curtailed using a new set of set pointschedules. Other techniques for providing recommended set points include(a) a rule-based suggestion, such as, a suggestion to move one or moreset points to be incrementally (e.g., 1 or 2 degrees) more efficient, ormaking the number of degrees suggested to be proportional to a“projected remaining use” and (b) using linear regression or a similarscheme that predicts a number of degrees to alter a set point schedule,for example, based on past usage.

Other recommendations may be directed to other energy usage componentson the property (e.g., time shifting washer/dryer usage, turning offlights, closing/opening windows when outside conditions satisfy certaincharacteristics, etc.). According to some implementations, the computingdevice may automatically adjust settings on the thermostat to modifyusage so that actual usage can remain within the budgeted use for thespecified budget period.

In view of the process 200, consider the following fact scenario:

(a) Customer base-load coefficient: 21.2 kwh/day

(b) Customer cooling degree day coefficient: 1.93 kwh/cdd/day

(c) Customer heating degree day coefficient: 0.51 kwh/hdd/day

(d) Days into billing period: 11

(e) Expected length of billing period: 30 days

(f) Cooling degree days in billing period (sum of number of degreesbelow a cooling temperature threshold, e.g., 65 degrees F.): 247

(g) Heating degree days in billing period (sum of number of degreesabove a heating temperature threshold): 0

(h) Forecasted usage to date:(a)*(d)+(b)*(f)/(d)+(c)*(g)/(d)=21.2*11+1.93*247/11+0.51*0/11=277 kwh

(i) Forecasted usage at end of billing period: 277 kwh/11 days*30days=754 kwh

One alternative embodiment uses both retrospective (described above withrespect to FIG. 2) and prospective weather data, as will be discussed inFIG. 3. In this example, the energy consumption to date would becalculated as described above. Rather than simply scaling this value upby the number of days left in the billing period, the embodiment woulduse forecasted weather conditions and the same disaggregationcoefficients to predict energy consumption through the end of thebilling period. The same logic can be used for deciding whether todeliver an alert to a customer after a forecast was made. In anotheralternative embodiment, prospective weather data may be used to predictenergy consumption for a billing period (with or without the use ofretrospective weather data). Accordingly, unusual usage projection maybe determined even before a billing period begins.

FIG. 3 illustrates a flowchart of an example process 300 for generatingenergy usage alerts in the energy usage alert system described inFIG. 1. The example process 300 is provided as an example and additionalor fewer steps may be performed, in similar or alternative orders, or inparallel, without departing from the scope of this specification.

In step 310, the computing device can determine a first forecasted usagefor a first portion of a billing period, based on a set of climatecontrol disaggregation coefficients and first weather data (e.g., knownweather data for a previous portion of the billing period).Additionally, the computing device can determine the first weather datacorresponding to the first portion of the billing period.

In step 320, the computing device can determine a second forecastedusage for a second portion of the billing period, based on the set ofclimate control disaggregation coefficients and the second weather data,e.g., that is provided by a weather forecast and, for example, receivedfrom a third-party service using API. In this example, the secondportion is subsequent in time to the first portion. The computing devicecan determine (receive) the second weather data corresponding to thesecond portion of the billing period (i.e., the remaining portion of thebilling period). The first weather data may be different from the secondweather data.

In step 330, the computing device can determine an unusual energy usageprojection for the particular utility customer, based at least in parton a combination of the first forecasted usage and the second forecastedusage being greater than usage data for a prior time periodcorresponding to the billing period.

In step 340, the computing device can generate an alert notificationincluding an indication of the unusual energy usage projection. In thisexample, the alert notification may be sent to the utility customerprior to the end of the billing period.

Consider the same fact scenario above, but with the following additionaldata:

(j) Forecast remaining days in billing period: 19

(k) Forecast cooling degree days in billing period: 428

(l) Forecast heating degree days in billing period: 0

Forecast energy usage at end of billing period:(h)+(a)*(j)+(b)*(k)/(j)+(c)*(l)/(j)=277+21.2*19+1.93*428/19+0.51*0/19=446kwh

Another alternative embodiment would compare the results of the approachdiscussed in FIG. 3 or FIG. 2 with a bill forecast created using smartmeter data as will be discussed in FIG. 4. While the smart meter datacan provide a more accurate bill prediction, it may not explain why autility customer's usage might be high.

By way of example, if both the smart meter bill forecast and billingdata+weather bill forecast indicated a high bill, the likely root causewas extreme weather. That is, high billing predictions that are based onabnormal weather data (or estimates), may indicate a higher usage (ascompared to a previous reference usage amount); however, the forecastedusage amount may not be considered to be unusually high, given thepredictable increase in energy consumption due to extreme cold/hotconditions.

Alternatively, if the billing data+weather bill forecast did notindicate a high bill, but the smart meter bill forecast did indicate ahigh bill, it could be deduced that the high usage was a result ofsomething other than weather/climate control (e.g. a guest staying inthe home). In some aspects, this intelligence can be used to improveupon the high usage alert delivered to the customer, for example, byproviding the utility customer a potential explanation for the highbill, and more targeted tips.

FIG. 4 illustrates a flowchart of an example process 400 for energyusage alerts in the energy usage alert system described in FIG. 1,according to certain aspects of the subject technology. Process 400 isprovided as an example, however, additional or fewer steps may beperformed in similar or alternative orders, or in parallel, withoutdeparting from the scope of this specification. In particular, theprocess of FIG. 4 discloses how an energy use projection calculation canbe performed using actual usage data from a current billing period, forexample, that is collected using a smart meter configured to provide AMIdata.

In step 410, the computing device can determine first forecasted usagedata for a portion of a billing period, for example, based on a set ofclimate control disaggregation coefficients, weather data, and/or actualusage data for at least a portion of the first portion of the billingperiod. The set of climate control disaggregation coefficients may beassociated with energy consumption data of a commodity for a particularutility customer and/or with a specific location (e.g., building orresidence). The set of climate control disaggregation coefficients caninclude coefficients relating to a rate of energy consumption for acorresponding type of climate control. The computing device can obtain,for example, from at least one third party service provider, weatherdata corresponding to at least a portion of the billing period.

In step 420, the computing device can determine second forecasted usagedata for a length of the billing period based at least in part on thefirst forecasted usage data. In some aspects, weather forecastinformation (e.g., for a number of future days) can be used to determinethe second forecasted usage data.

In step 430, the computing device can determine an actual usageprojection for the utility customer. In some aspects, the actual usageprojection is based on smart meter data, such as, AMI data reflectingpower use for one or more days of the current billing period. In thisexample, the unusual energy usage projection is indicative of theutility customer projected to receive a high utility bill.

In step 440, the computing device can determine that the actual usageprojection indicates that an upcoming utility bill for the particularutility customer is greater than a threshold (i.e., that the actualusage projection is considered to be ‘unusual energy use’). The actualusage projection is data based on smart meter data collected, forexample, using an AMI metering infrastructure. In this example, thethreshold can be a predetermined amount (e.g., indicated as a percentageincrease in the total bill amount). Alternatively, the threshold may bea predefined user configurable value set by the utility customer totrigger an alert. The threshold value may be indicated as a monetaryvalue or an energy amount, depending on implementation.

An actual usage projection can relate to actual usage data of a currentbilling cycle, as opposed to historic data from previous periods. Actualusage projections can be based on scaled projections for actual usagedata from the current period. For example, in a 30 day period in whichactual usage data is available for the first 10 days, an actual usageprojection may be equivalent to the energy consumption for the first 10days, scaled by a factor of 3.

In step 450, the computing device can generate an alert notificationincluding an indication of the unusual energy usage projection. Theindication can include information relating to a cause for an increasein the utility bill based on the unusual energy usage projection. Forexample, if it is determined that the unusual energy usage projection isdue to abnormal weather (e.g., either unusually hot or cold weather),then the cause (weather) may be provided to the customer as a reason forthe unusual high energy consumption amount. Alternatively, if theweather conditions are not abnormal, various energy conservation tipsmay be provided to help the customer to lower their projected usageconsumption. By way of example, recommended thermostat set points may beindicated, which would enable the user to reduce his/her energyconsumption for a remaining portion of the current billing period.

FIGS. 5A-5C illustrates examples of energy usage alert notifications,according to certain aspects of the subject technology. In FIG. 5A, anexample of an energy usage alert notification 500 is illustrated. Energyusage alert notification 500 includes utility identifier 502, accountnumber 504, alert title 506, report analysis 508, report message 510,and recommendation portion 512. Energy usage alert notification 500 isprovided merely as an example and additional or fewer features may beincluded in similar or alternative formats within the scope of thevarious embodiments described in this specification.

Utility identifier 502 may relate to the utility company associated withthe generation of the energy usage alert notification 500. Utilityidentifier 502 may include a name of the utility company, an address forthe utility company, and/or contact information for the utility company.

The account number 504 may relate to the corresponding utility customersubscribed to receive energy usage alerts such as the energy usage alertnotification 500. For privacy reasons, account number 504 may be limitedto a subset of numbers that, at least in part, identify the utilityaccount without including any personal or identifying information of theaccount holder. In an aspect, account number 504 is displayed in itsentirety.

The alert title 506 provides an identification of the type ofnotification contained in the energy usage alert notification 500. Forexample, the alert title 506 may relate to a power conservation alertwhere the notification 500 provides the utility customer an indicationon how to save energy and/or money for the current billing period. Inthis example, the energy usage alert notification 500 may be sent to theutility customer before the end of the current billing period to allowthe utility customer sufficient time to make adjustments to currentclimate control settings of the corresponding property. Energy usagealert notification 500 may be generated and sent to the utility customerbefore the end of the billing period even if usage interval data is notavailable for the site of the utility customer using the approachesdiscussed in FIGS. 2-4.

The report analysis 508 may include information relating to how thecurrent projected bill compares to prior utility bills, and may includea metric to give the utility customer some context to the currentprojected bill. The report analysis 508 may include additional metricssuch as a chart to provide the utility customer a visual analysis of thecurrent projected bill.

The report message 510 may include an indication to the utility customerthat the projected bill can still be altered if certain adjustments aremade prior to the end of the current billing period. The report message510 also may include other report messages relating to the currentprojected bill such as usage information relating to specific componentsof the property and/or rate information over the duration of thespecified billing period.

The recommendation portion 512 may include recommendations on how tomodify usage so that actual usage can remain within a desired monetaryrange for the specified billing period. The recommendations may includeset points or set point schedules that may be used on the climatecontrol device, such as, suggestions to turn off light sources and/orelectronic devices, maintenance suggestions, and specific adjustments tothe climate control device.

In FIG. 5B, an example of an energy usage alert notification 520 isillustrated. The energy usage alert notification 520 includes a utilityidentifier 502, an account number 504, an alert title 506, an alertmessage 522, a geo-based climate message 524, and a comparison chart526.

The alert message 522 includes an indication to the utility customerthat the utility bill for the specified billing period is projected tobe higher than expected. In this example, the projection may indicatethat the cost of energy consumption is higher for a current billingperiod compared to the same calendar period of a prior year. The alertmessage 522 can include one or more icons and/or symbols representing analert to the utility customer. In some aspects, the alert message 522includes an indication of recommended steps to reduce the projectedenergy cost prior to the end of the specified billing period.

The geo-based climate message 524 includes information relating to theclimate of a corresponding location (e.g., zip code) compared to ahistorical average for that location. In some aspects, the geo-basedclimate message 524 includes an indication of whether the climate forthe specified billing period is cooler or hotter than the historicalaverage. In this example, the geo-based climate message 524 indicatesthat the climate of the specified billing period (e.g. month of August)is hotter than normal. In this respect, any increase in energyconsumption for the specified billing period is likely correlated to anincrease in temperature for the corresponding location.

The comparison chart 526 includes a two-dimensional chart includinginformation relating to a trend of the cost for energy consumption overa specified calendar range. In this example, the x-axis indicates anumber of months for the specified calendar range and the y-axisindicates a cost range for the energy consumption. For example, themonth of June experienced an average of high temperatures thattranslated to a cost $100. Similarly, the month of August experiencedhigher than normal temperatures, which is projected to cost the utilitycustomer about $99. In this regard, the projected cost is likely due tothe increasing temperatures for the month of August.

In FIG. 5C, an example of an energy usage alert notification 540 isillustrated. The energy usage alert notification 540 includes a utilityidentifier 502, an account number 504, an alert message 542, and acomparison chart 544.

The alert message 542 includes an indication to the utility customerthat the utility bill for the specified billing period is projected tobe lower compared to the same period in prior years. In this example,the projection may indicate that the cost of energy consumption islikely to be lower for a current billing period due to the weatherforecasted to be cooler to thereby avoid a need to cool down theproperty of the utility customer. The alert message 542 can include oneor more icons and/or symbols with a corresponding notification. In someaspects, the alert message 542 includes an indication of how much energyis being saved from consumption or how much in monetary value isprojected to be saved in the utility bill.

The comparison chart 544 includes two-dimensional charts indicating acost in energy consumption for two different calendar periods. In thisexample, the cost in energy consumption for a specified period (e.g.,May) in a prior year (2013) is greater than the cost projected for thesame period in the specified billing period (May 2014). In some aspects,the comparison chart 544 includes the comparison in terms of the amountof energy (e.g., 156 kWh versus 103 kWh).

The subject technology allows for identifying customers whose energyconsumption is particularly sensitive to weather, and use hourly ordaily weather data as a proxy for energy consumption data that iscollected monthly. In this regard, the subject technology relies oncustomer specific sensitivity to weather conditions to decide whether ornot an alert should be delivered. It would be trivial to deliver alertsto all customers after several days of especially cold or hot weather,but there would be many false positives in that case as utilitycustomers whose consumption is not correlated with temperatures wouldnot be more likely to have an abnormal bill.

FIG. 6 illustrates an example of an environment 600 for implementingaspects in accordance with various embodiments. Environment 600 includesutility company 601, power distribution system 602, utility customerregions 610, 620 and 630, energy usage collector 640, network 650 andusage alert system 660. The utility customer region 610 includesresidential structures with corresponding smart meters 611-614. Theutility customer region 620 includes commercial structures withcorresponding smart meters 621-623. The utility customer region 630includes multi-family structures with corresponding smart meters631-633. The usage alert system 660 includes a web server 661, anapplication server 662 and a database 663.

Utility company 601 provides a commodity (e.g., electricity, gas, water)to utility customer regions 610, 620 and 630, and can track the energyusage from each region via a monitoring device (e.g., a meter)associated with each structure of the corresponding region. The utilitycompany 601 may receive usage data that includes the amount of energyconsumption (e.g., kWh) for the corresponding utility account. In anaspect, the utility company 601 receives the usage data from the energyusage collector 640 via a wireless communication system. In someaspects, the energy usage collector 640 may obtain the usage data bypulling the usage data from each of the metering devices, or the usagedata may be collected manually by regular meter readings, for example,on a monthly, weekly or bi-weekly basis. The utility company 601 alsomay receive the usage data from each monitoring device through a wiredcommunication system.

The usage alert system 660 is in communication with the utility company601 via the network 650. The usage alert system 660 may obtain the usagedata from the utility company 601 via the network 650. In an aspect,usage alert system 660 receives the usage data via the network 650. Theusage alert system 660 may receive the usage data directly from themeter devices.

Each of the utility customer regions 610, 620 and 630 may correspond toa separate geographical location with a respective rate schedule. Insome aspects, an energy usage alert notification for a correspondingutility customer in one region may be generated using usage data forsimilar users in the same (or a similar) region to provide thecorresponding utility customer with a comparative analysis of its energyconsumption (e.g., current energy usage compared to similar customers inthe same zip code or within a certain radius).

The usage alert system 660 also may be in communication with a thirdparty weather service, such as the National Weather Service (not shown).For example, usage alert system 660 may receive corresponding outdoortemperatures from the third party weather service via the network 650(e.g., e-mails, downloaded FTP files, and XML feeds). In this respect,usage alert system 660 may use data from the third party weather serviceto determine a projected use for a current billing period. For example,forecasted weather conditions (e.g., the temperature, the humidity, thebarometric pressure, precipitation, etc.) may indicate that the utilitycustomer's HVAC system is likely to be in greater use. The usage alertsystem 660 may estimate the projected use for the remaining amount oftime of the current billing period, and thereby determine if the utilitycustomer is on pace to exceed the projected bill based on the estimatedprojected use. In turn, usage alert system 660 may notify the utilitycustomer through an energy usage alert notification.

Usage alert system 660 communicates the energy usage alert notificationto utility customers associated with the utility customer regions 610,620 and 630. In some aspects, usage alert system 660 communicates theenergy usage alert notification via network 650. For example, usagealert system 660 may send the energy usage alert notification in ane-mail or the utility customer may log into usage alert system 660(e.g., the web server 661 and/or application server 662) through anassociated website to view the disaggregated usage data included in theenergy usage alert notification. The usage alert system 660 may send theenergy usage information to a printing system so that the energy usagealert notification can be provided to the utility customer via regularmail (e.g., as part of a utility bill). In other aspects, the energyusage information is communicated back to the utility company 601 suchthat the utility company 601 can provide the energy usage alertnotification to the utility customer.

FIG. 7 illustrates an example of a system 700 for energy usage alerts,according to certain aspects of the subject technology. Although aweb-based environment is described for purposes of explanation,different environments may be used, as appropriate, to implement variousembodiments.

The example system 700 includes a usage alert system 705 and a dataplane 710. The usage alert system 705 includes at least one web server706 and at least one application server 708, as described below. Theusage alert system 705 is an example of an energy usage notificationsystem implemented as computer programs on one or more computers in oneor more locations, in which the systems, components, and techniquesdescribed below can be implemented.

A user can interact with the usage alert system 705 through a clientdevice 702. For example, the client device 702 can be a computer coupledto the usage alert system 705 through a data communication network 704,e.g., the Internet. In some instances, the usage alert system 705 can beimplemented on the client device 702, for example, through a softwareapplication executing on the client device 702. The client device 702generally includes a memory, e.g., a random access memory (RAM), forstoring instructions and data, and a processor for executing storedinstructions. The client device 702 can be any appropriate deviceoperable to send and receive requests, messages, or other types ofinformation over the data communication network 704. The client device702 can also include a display screen though which the user interactingwith the client device 702 can view information, e.g., energy usagealert notification 300 of FIG. 3. Some examples of client devicesinclude personal computers, smart thermostats, cellular phones, handheldmessaging devices, laptop computers, set-top boxes, personal dataassistants, electronic book readers, tablet devices, smartphones and thelike.

The data communication network 704 can include any appropriate network,including an intranet, the Internet, a cellular network, a local areanetwork, a wide area network, or any other such network, or combinationthereof. Components used for such a system can depend at least in partupon the type of network, the environment selected, or both. Protocolsand components for communicating over such a network are well known andwill not be discussed herein in detail. The client device 702 cancommunicate over the data communication network 704 using wired orwireless connections, and combinations thereof.

A user can use the client device 702 to submit a request 720 to log intothe usage alert system 705. The request 720 can request a digital copyof an energy usage alert notification for a corresponding utilityaccount. The energy usage alert notification may include informationrelating to how much energy has been consumed to date and/or a projectedbill amount for a current billing period. The usage alert notificationalso can include information relating to one or more recommendations foradjusting settings in the property associated with the correspondingutility account such that the projected bill is kept below a targetbudget for the current billing period. When the user submits the request720, the request 720 may be transmitted through the data communicationnetwork 704 to the application server 708 within the usage alert system705. The application server 708 responds to the request 720 by using,for example, usage data 712, to identify data 722 describing an energyusage alert with personalized information in response to the request720. The application server 708 sends the data 722 through the datacommunication network 704 to the client device 702 for presentation tothe user.

The data 722 can include data describing a projected bill for a currentbilling period. The data 722 can be used, for example, by the clientdevice 702, to generate a local energy usage alert notification with oneor more interactive features such as energy consumption adjustments withcorresponding utility bill projections and/or instructions for adjustingsettings on a climate control device associated with the correspondingutility customer.

After receiving the data 722 from the application server 708, andthrough the data communication network 704, a software application,e.g., web browser or application 724, running on the client device 702renders an interactive energy usage alert notification using the data722. For example, a usage engine 726 in the application 724 can describethe usage to date including a projected use for the current billingperiod, for display on a display screen of the client device 702.

In some aspects, the application 724 includes a climate control engine728 that is configured to render an interface to the climate controldevice, and perform one or more actions related to the instructions foradjusting the settings of the climate control device. In someembodiments, the climate control engine 728 is configured to obtain datarelating to current settings of the climate control device. The climatecontrol engine 728 can obtain real-time statistics and/or sensorreadings (e.g., thermometer reading) of current climate conditions inthe property. In an aspect, the application 724 includes an alert engine730 that is configured to render the energy usage alert notificationincluding allow the user to set (or program) rules and/or conditions forreceiving the energy usage alert notification.

In some embodiments, the web server 706, the application server 708, andsimilar components, can be considered to be part of the data plane 710.The handling of all requests and responses, as well as the delivery ofcontent between the client device 702 and the application server 708,can be handled by the web server 706. The web server 706 and theapplication server 708 are merely example components. However, more orfewer components can be used as structured code can be executed on anyappropriate device or host machine as discussed elsewhere herein.

The data plane 710 includes one or more resources, servers, hosts,instances, routers, switches, data stores, other similar components, ora combination thereof. The resources of the data plane 710 are notlimited to storing and providing access to data. Indeed, there may beseveral servers, layers, or other elements, processes, or components,which may be chained or otherwise configured, and which can interact toperform tasks including, for example, obtaining data from an appropriatedata store. In some embodiments, the term “data store” refers to anydevice or combination of devices capable of storing, accessing, andretrieving data, which may include any combination and number of dataservers, databases, data storage devices, and data storage media, in anystandard, distributed, or clustered environment.

The data stores of the data plane 710 can include several separate datatables, databases, or other data storage mechanisms and media forstoring data relating to a particular aspect. For example, the dataplane 710 illustrated includes mechanisms for storing usage data 712 anduser information 716, which can be used to generate the energy usagealert notification. The data plane 710 is also shown to include amechanism for storing similar user data 714, which can be used forpurposes such as reporting a comparative analysis of the usage data forthe corresponding utility customer. The data plane 710 is operable,through logic associated therewith, to receive instructions from theapplication server 708 and to obtain, update, or otherwise process data,instructions, or other such information in response thereto, asdescribed above.

Each server typically includes an operating system that providesexecutable program instructions for the general administration andoperation of that server, and typically will include a computer-readablemedium storing instructions that, when executed by a processor of theserver, enable the server to perform its intended functions. Suitableimplementations for the operating system and general functionality ofthe servers are known or commercially available, and are readilyimplemented by persons having ordinary skill in the art, particularly inlight of the disclosure herein.

The environment in one embodiment is a distributed computing environmentincluding several computer systems and components that areinterconnected through one or more communication links, using one ormore computer networks or direct connections. However, the systemdescribed above can be configured to operate equally well using fewer ora greater number of components than are illustrated in FIG. 7. Thus, thesystem 700 in FIG. 7 is provided merely as one example, and does notlimit the scope of the disclosure.

FIG. 8 illustrates an example configuration of components of a computingdevice 800, e.g., the climate control devices 103 a-103 n of FIG. 1,according to certain aspects of the subject technology. In this example,the computing device 800 includes a processor 802 for executinginstructions that can be stored in a memory device or element 804. Theinstructions may cause the computing device 800 to execute acomputer-implemented method for processing energy usage alerts from theenergy usage alert system 100 (FIG. 1) and/or receive instructions toautomatically adjust settings (e.g., temperature settings, alarmsettings, power settings) of the client computing device 800. As wouldbe apparent to one of ordinary skill in the art, the computing device800 can include many types of memory, data storage, or non-transitorycomputer-readable storage media, such as a first data storage forprogram instructions for execution by the processor 802, a separatestorage for usage history or user information, a removable memory forsharing information with other devices, etc. In some embodiments, thecomputing device 800 can include one or more communication components806, such as a Wi-Fi, Bluetooth®, radio frequency, near-fieldcommunication, wired, or wireless communication system. The computingdevice 800 in many embodiments can communicate with a network, such asthe Internet, and may be able to communicate with other such devices(e.g., the energy usage alert system 100, other climate controldevices). As discussed, the computing device 800 in many embodimentswill include at least one input element 808 able to receive conventionalinput from a user. This conventional input can include, for example, apush button, touch pad, touch screen, wheel, joystick, keyboard, mouse,keypad, or any other such device or element whereby a user can input acommand to the device. In some embodiments, however, such a device mightnot include any buttons at all, and might be controlled only through acombination of visual and audio commands, such that a user can controlthe device without having to be in contact with the device. Thecomputing device 800 includes some type of display element 810, such asa touch screen or liquid crystal display (LCD).

The various embodiments can be implemented in a wide variety ofoperating environments, which in some cases can include one or more usercomputers, computing devices, or processing devices which can be used tooperate any of a number of applications. User or client devices caninclude any of a number of general purpose personal computers, such asdesktop or laptop computers running a standard operating system, as wellas cellular, wireless, and handheld devices running mobile software andcapable of supporting a number of networking and messaging protocols.Such a system also can include a number of workstations running any of avariety of commercially-available operating systems and other knownapplications for purposes such as development and database management.These devices also can include other electronic devices, such as dummyterminals, thin-clients, gaming systems, and other devices capable ofcommunicating via a network.

Various aspects also can be implemented as part of at least one serviceor Web service, such as may be part of a service-oriented architecture.Services such as Web services can communicate using any appropriate typeof messaging, such as by using messages in extensible markup language(XML) format and exchanged using an appropriate protocol such as SOAP(derived from the “Simple Object Access Protocol”). Processes providedor executed by such services can be written in any appropriate language,such as the Web Services Description Language (WSDL). Using a languagesuch as WSDL allows for functionality such as the automated generationof client-side code in various SOAP frameworks.

Most embodiments utilize at least one network that would be familiar tothose skilled in the art for supporting communications using any of avariety of commercially-available protocols, such as TCP/IP, OSI, FTP,UPnP, NFS, and CIFS. The network can be, for example, a local areanetwork, a wide-area network, a virtual private network, the Internet,an intranet, an extranet, a public switched telephone network, aninfrared network, a wireless network, and any combination thereof.

In embodiments utilizing a Web server, the Web server can run any of avariety of server or mid-tier applications, including HTTP servers, FTPservers, CGI servers, data servers, Java servers, and business mapservers. The server(s) also may be capable of executing programs orscripts in response requests from user devices, such as by executing oneor more Web applications that may be implemented as one or more scriptsor programs written in any programming language, such as Java®, C, C# orC++, or any scripting language, such as Perl, Python, or TCL, as well ascombinations thereof. The server(s) may also include database servers,including without limitation those commercially available from Oracle®,Microsoft®, Sybase®, and IBM®.

The environment can include a variety of data stores and other memoryand storage media as discussed above. These can reside in a variety oflocations, such as on a storage medium local to (and/or resident in) oneor more of the computers or remote from any or all of the computersacross the network. In a particular set of embodiments, the informationmay reside in a storage-area network (“SAN”) familiar to those skilledin the art. Similarly, any necessary files for performing the functionsattributed to the computers, servers, or other network devices may bestored locally and/or remotely, as appropriate. Where a system includescomputerized devices, each such device can include hardware elementsthat may be electrically coupled via a bus, the elements including, forexample, at least one central processing unit (CPU), at least one inputdevice (e.g., a mouse, keyboard, controller, touch screen, or keypad),and at least one output device (e.g., a display device, printer, orspeaker). Such a system may also include one or more storage devices,such as disk drives, optical storage devices, and solid-state storagedevices such as random access memory (“RAM”) or read-only memory(“ROM”), as well as removable media devices, memory cards, flash cards,etc.

Such devices also can include a computer-readable storage media reader,a communications device (e.g., a modem, a network card (wireless orwired), an infrared communication device, etc.), and working memory asdescribed above. The computer-readable storage media reader can beconnected with, or configured to receive, a computer-readable storagemedium, representing remote, local, fixed, and/or removable storagedevices as well as storage media for temporarily and/or more permanentlycontaining, storing, transmitting, and retrieving computer-readableinformation. The system and various devices also typically will includea number of software applications, modules, services, or other elementslocated within at least one working memory device, including anoperating system and application programs, such as a client applicationor Web browser. It should be appreciated that alternate embodiments mayhave numerous variations from that described above. For example,customized hardware might also be used and/or particular elements mightbe implemented in hardware, software (including portable software, suchas applets), or both. Further, connection to other computing devicessuch as network input/output devices may be employed.

Storage media and computer readable media for containing code, orportions of code, can include any appropriate media known or used in theart, including storage media and communication media, such as but notlimited to volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information such as computer readable instructions, data structures,program modules, or other data, including RAM, ROM, EEPROM, flash memoryor other memory technology, CD-ROM, digital versatile disk (DVD) orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe a system device. Based on the disclosure and teachings providedherein, a person of ordinary skill in the art will appreciate other waysand/or methods to implement the various embodiments.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the disclosure asset forth in the claims.

The description of the subject technology is provided to enable anyperson skilled in the art to practice the various embodiments describedherein. While the subject technology has been particularly describedwith reference to the various figures and embodiments, it should beunderstood that these are for illustration purposes only and should notbe taken as limiting the scope of the subject technology.

There may be many other ways to implement the subject technology.Various functions and elements described herein may be partitioneddifferently from those shown without departing from the scope of thesubject technology. Various modifications to these embodiments will bereadily apparent to those skilled in the art, and generic principlesdefined herein may be applied to other embodiments. Thus, many changesand modifications may be made to the subject technology, by one havingordinary skill in the art, without departing from the scope of thesubject technology.

A reference to an element in the singular is not intended to mean “oneand only one” unless specifically stated, but rather “one or more.” Theterm “some” refers to one or more. Underlined and/or italicized headingsand subheadings are used for convenience only, do not limit the subjecttechnology, and are not referred to in connection with theinterpretation of the description of the subject technology. Allstructural and functional equivalents to the elements of the variousembodiments described throughout this disclosure that are known or latercome to be known to those of ordinary skill in the art are expresslyincorporated herein by reference and intended to be encompassed by thesubject technology.

What is claimed is:
 1. A computer-implemented method for unusual usagealert notifications without smart meter data, the method comprising:determining a set of climate control disaggregation coefficientsassociated with energy consumption data of a commodity for a particularutility customer, the set of climate control disaggregation coefficientsincluding one or more coefficients relating to a rate of energyconsumption for a corresponding type of climate control; obtaining, fromat least one third party service provider, weather data corresponding toat least a portion of a billing period; determining first forecastedusage data for the at least a portion of the billing period based atleast in part on the set of climate control disaggregation coefficientsand the weather data; determining second forecasted usage data for alength of the billing period based at least in part on the firstforecasted usage data, the length of the billing period being greaterthan the at least a portion of the billing period; determining anunusual energy usage projection for the particular utility customerbased at least in part on the second forecasted usage data being greaterthan a threshold usage; and generating an alert notification includingan indication of the unusual energy usage projection.
 2. Thecomputer-implemented method of claim 1, further comprising: sending thealert notification to the particular utility customer, the unusualenergy usage projection relating to a likelihood of the particularutility customer projected to receive a utility bill higher thanexpected.
 3. The computer-implemented method of claim 1, wherein the setof climate control disaggregation coefficients comprises a base-loadcoefficient, a cooling coefficient and a heating coefficient.
 4. Thecomputer-implemented method of claim 3, wherein the first forecastedusage data is determined using an expression defined asperiod_to_date_days*coefficient_(base-load)+period_to_date_cooling_degree_days*coefficient_(cooling)period_to_date_heating_degree_days*coefficient_(heating), where theperiod_to_date_days corresponds to the number of days into the billingperiod, the period_to_date_cooling_degree_days is the number of degreesrelated to cooling by the commodity per day with respect to atemperature threshold, period_to_date_heating_degree_days is the numberof degrees related to heating by the commodity per day with respect tothe temperature threshold, the coefficient_(base-load) is the base-loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.
 5. Thecomputer-implemented method of claim 1, further comprising: applying arate structure to the second forecasted usage data to determine aforecasted bill amount corresponding to the length of the billingperiod, wherein the unusual energy usage projection for the particularutility customer is based at least in part on the forecasted bill amountbeing greater than a bill amount for the prior time period.
 6. Thecomputer-implemented method of claim 1, wherein determining the secondforecasted usage data comprises scaling the first forecasted usage databy a number of days corresponding to the length of the billing period.7. A computing device for energy usage alerts, the computing devicecomprising: at least one processor; and memory storing instructionsthat, when executed by the at least one processor, cause the computingdevice to: determine a first forecasted usage for a first portion of thebilling period based on a set of climate control disaggregationcoefficients and first weather data, the set of climate controldisaggregation coefficients including one or more coefficients relatingto a rate of energy consumption for a corresponding type of climatecontrol; determine a second forecasted usage for a second portion of thebilling period based on the set of climate control disaggregationcoefficients and second weather data, the second portion beingsubsequent in time of the first portion; determine an unusual energyusage projection based at least in part on a combination of the firstforecasted usage and the second forecasted usage being greater than athreshold usage data; and generate an alert notification including anindication of the unusual energy usage projection.
 8. The computingdevice of claim 7, wherein the instructions further cause the computingdevice to: send the alert notification to the particular utilitycustomer, the unusual energy usage projection relating to a likelihoodof the particular utility customer projected to receive a utility billhigher than expected.
 9. The computing device of claim 7, wherein theset of climate control disaggregation coefficients comprises a base-loadcoefficient, a cooling coefficient and a heating coefficient.
 10. Thecomputing device of claim 9, wherein the first forecasted usage data isdetermined using an expression defined asperiod_to_date_days*coefficient_(base-load)+period_to_date_cooling_degree_days*coefficient_(cooling)+period_to_date_heating_degree_days*coefficient_(heating),where the period_to_date_days corresponds to the number of days into thebilling period, the period_to_date_cooling_degree_days is the number ofdegrees related to cooling by the commodity per day with respect to atemperature threshold, period_to_date_heating_degree_days is the numberof degrees related to heating by the commodity per day with respect tothe temperature threshold, the coefficient_(base-load) is the base loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.
 11. The computingdevice of claim 9, wherein the second forecasted usage data isdetermined using an expression defined asremaining_days*coefficient_(base-load)(forecast_cooling_degree_days/remaining_days)*coefficient_(cooling)(forecast heating_degree_days/remaining_days)*coefficient_(heating),where the remaining_days is the second portion corresponding to thenumber of days remaining in the billing period, theforecast_cooling_degree_days is the projected number of degrees relatedto cooling by the commodity per day with respect to a temperaturethreshold, forecast_heating_degree_days is the projected number ofdegrees related to heating by the commodity per day with respect to thetemperature threshold, the coefficient_(base-load) is the base-loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.
 12. The computingdevice of claim 7, wherein the instructions further cause the computingdevice to: apply a rate structure to the second forecasted usage data todetermine a forecasted bill amount corresponding to the length of thebilling period, wherein the unusual energy usage projection for theparticular utility customer is based at least in part on the forecastedbill amount being greater than a bill amount for the prior time period.13. The computing device of claim 7, wherein the instructions furthercause the computing device to: determine an actual usage projectionbased on actual usage data associated with one or more utility customerssimilar to the particular utility customer; and determine whether theunusual energy usage projection and the actual usage projection indicatea utility bill for the particular utility customer is greater thanprojected, wherein the indication included in the alert notificationcomprises first information indicating an increase in the utility billis due to weather if both actual usage projection and the unusual energyusage projection indicate the utility bill is greater than projected,and wherein the indication comprises second information indicating anincrease in the utility bill is due to non-weather conditions if theactual usage projection indicates the utility bill is greater thanprojected and not the unusual energy usage projection.
 14. Anon-transitory computer readable storage medium storing instructions forunusual usage alerts without smart meter data on a computing device, theinstructions when executed by a processor causing the processor to:determine first forecasted usage data relating to a particular utilitycustomer for at least a portion of a billing period based at least inpart on a set of climate control disaggregation coefficients and weatherdata, the set of climate control disaggregation coefficients includingone or more coefficients relating to a rate of energy consumption for acorresponding type of climate control, the weather data obtained from atleast one third party service provider; determine second forecastedusage data for a length of the billing period based at least in part onthe first forecasted usage data; determine an unusual energy usageprojection based at least in part on the second forecasted usage databeing greater than usage data for a prior time period corresponding tothe billing period; determine that at least one of the unusual energyusage projection or an actual usage projection indicate a projectedutility bill for the particular utility customer is greater than athreshold, the actual usage projection relating to actual usage dataassociated with one or more utility customers similar to the particularutility customer; and generate an alert notification including anindication of the unusual energy usage projection, the indicationincluding information relating to a cause for an increase in the utilitybill based on the unusual energy usage projection or the actual usageprojection determined to be greater than the threshold.
 15. Thenon-transitory computer readable storage medium of claim 14, wherein theinstructions further cause the computing device to: send the alertnotification to the particular utility customer, the unusual energyusage projection relating to a likelihood of the particular utilitycustomer projected to receive a utility bill higher than expected. 16.The non-transitory computer readable storage medium of claim 14, whereinthe set of climate control disaggregation coefficients comprises abase-load coefficient, a cooling coefficient and a heating coefficient.17. The non-transitory computer readable storage medium of claim 16,wherein the first forecasted usage data is determined using anexpression defined as period_to_date_days*coefficient_(base-load)period_to_date_cooling_degree_days*coefficient_(cooling)+period_to_date_heating_degree_days*coefficient_(heating),where the period_to_date_days corresponds to the number of days into thebilling period, the period_to_date_cooling_degree_days is the number ofdegrees related to cooling by the commodity per day with respect to atemperature threshold, period_to_date_heating_degree_days is the numberof degrees related to heating by the commodity per day with respect tothe temperature threshold, the coefficient_(base-load) is the base-loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.
 18. Thenon-transitory computer readable storage medium of claim 16, wherein thesecond forecasted usage data is determined using an expression definedasremaining_days*coefficient_(base-load)+(forecast_cooling_degree_days/remaining_days)*coefficient_(cooling)(forecast heating_degree_days/remaining_days)*coefficient_(heating),where the remaining_days is the second portion corresponding to thenumber of days remaining in the billing period, theforecast_cooling_degree_days is the projected number of degrees relatedto cooling by the commodity per day with respect to a temperaturethreshold, forecast_heating_degree_days is the projected number ofdegrees related to heating by the commodity per day with respect to thetemperature threshold, the coefficient_(base-load) is the base-loadcoefficient, the coefficient_(cooling) is the cooling coefficient, andthe coefficient_(heating) is the heating coefficient.
 19. Thenon-transitory computer readable storage medium of claim 14, wherein theinstructions further cause the computing device to: apply a ratestructure to the second forecasted usage data to determine a forecastedbill amount corresponding to the length of the billing period, whereinthe unusual energy usage projection for the particular utility customeris based at least in part on the forecasted bill amount being greaterthan a bill amount for the prior time period.
 20. The non-transitorycomputer readable storage medium of claim 14, wherein the indicationincluded in the alert notification comprises first informationindicating an increase in the utility bill is due to weather if bothactual usage projection and the unusual energy usage projection indicatethe utility bill is greater than projected, and wherein the indicationcomprises second information indicating an increase in the utility billis due to non-weather conditions if the actual usage projectionindicates the utility bill is greater than projected and not the unusualenergy usage projection.
 21. A computer-implemented method for providingan unusual power consumption alert notification, the method comprising:calculating a first forecasted usage amount for a first portion of acurrent billing period, wherein the first forecasted usage amount isdetermined based on a set of climate control disaggregation coefficientsand historic weather data corresponding with the first portion of thecurrent billing period; calculating a second forecasted usage amount fora second portion of the current billing period, wherein the secondforecasted usage data is determined using forecasted weather data forthe second portion of the current billing period and the climate controldisaggregation coefficients; calculating an energy usage projection forthe current billing period based on the first forecasted usage amountand the second forecasted usage amount; determining whether the energyuse projection exceeds a predetermined threshold; and generating analert notification to indicate an unusual energy use projection inresponse to a determination that the energy use projection exceeds thepredetermined threshold.